1. Field of the Invention
The present invention relates to a delayed decision feedback sequence estimating and receiving apparatus for selecting an optimum region from an impulse response sequence of a transmission channel distortion to estimate a transmission signal. More particularly, the present invention relates to a delayed decision feedback sequence estimating and receiving apparatus for estimating a transmission signal from a signal containing transmission channel distortion caused due to a frequency selective fading phenomenon which occurs in multi-path propagation in a high speed digital communication system, for example, in a wireless communication channel in a digital mobile telephone system.
2. Description of the Related Art
Conventionally, "MAXIMUM LIKELIHOOD SEQUENCE ESTIMATING AND RECEIVING APPARATUS" described in Japanese Laid Open Patent Disclosures (JP-A-Heisei 5-292138 and JP-A-Heisei 5-292139) is well known as a signal estimating system in which a transmission signal is estimated while an optimum region is selected from a sequence of pulses of an impulse response representing a transmission path distortion.
FIG. 1 is a schematic block diagram for illustrating the structure of such a conventional maximum likelihood sequence estimator. Referring to FIG. 1, the conventional maximum likelihood sequence is composed of a matching filter 2, a state estimator 3, a coefficient setting unit 4, an estimating unit 5, a signal generating unit 6 and a position estimating unit 7.
In this conventional maximum likelihood sequence estimator, each of the tap coefficients of the matching filter 2 is applied based on a sequence of pulses of an impulse response of a reception signal received through a transmission channel. The state estimator 3 has the largest processing amount. Therefore, to suppress the processing amount of the state estimator 3, the number of taps of the matching filter 2 must be suppressed to a minimum amount. When the number of taps is reduced, only a partial region of the sequence of pulses of the impulse response can be processed.
As a result, the following determination is required. That is, the highest estimation capability may be achieved when any one of the regions for the sequence of pulses of the impulse response should be processed by using what tap coefficients. This determination of an estimation region is carried out by the maximum likelihood sequence estimator shown in FIG. 1. First, when a training signal is received, the signal generating unit 6 generates the same signal as the training signal provided from a transmission side, and supplies the same signal to the estimating unit 5. Thus, the impulse response of the transmission channel is calculated by the estimating unit 5.
FIG. 2 schematically illustrates a sequence of pulses of an impulse response. When the sequence of pulses of the impulse response shown in FIG. 2 are acquired, the pulse amplitude values are compared with each other by the position estimating unit 7 shown in FIG. 1. Then, these pulse amplitude values are respectively allocated with pulse numbers from the smallest number in the order of larger pulse amplitude value. As the optimum signal estimation region is recognized the region which has the smallest summation value of pulse numbers, among the regions containing the pulse having the maximum pulse amplitude value. A timing signal indicative of an optimum signal estimation region is outputted to the coefficient setting unit 4 such that the optimum tap coefficients are supplied to the matching filter 2. Also, the position estimating unit 7 outputs the timing signal to the state estimator 3. The state estimator 3 carries out the optimum maximum likelihood sequence estimation.
On the other hand, the delayed decision feedback sequence estimator is described in "NEC Research and Development" by Hitoshi Matsui, (January, 1997, pp. 74 to 79). The method for determining the signal estimation region used in the conventional maximum likelihood sequence estimator is similarly applied to the method for determining the signal estimation region in this delayed decision feedback sequence estimator.
However, the above-described conventional examples have the following two problems.
The first problem is in that, depending upon the impulse response waveform, the optimum signal estimation region estimated in the delayed decision feedback sequence estimator is not coincident with the optimum estimation region estimated in the maximum likelihood sequence estimator. In other words, when the conventional maximum likelihood sequence estimation method for determining the optimum signal estimation region is applied to the delayed decision feedback sequence estimation method, the optimum signal estimation region cannot be always determined. This problem will now be explained more in detail.
As indicated in FIG. 2, in the delayed decision feedback sequence estimator, it could be considered that a region of the impulse response used for performing the optimum signal estimation is divided into the region for the maximum likelihood sequence estimation and the region for decision feedback equalization. Since the pulses of the impulse response in the decision feedback equalization region are canceled through the decision feedback equalizing calculation, even when the large power pulses are present in this region, these pulses do not contribute to the optimum signal estimation. As a consequence, in accordance with the calculating method in which the maximum likelihood sequence estimation region and the decision feedback equalization region are combined with each other, the optimum signal estimation region is not always found out.
FIG. 3 schematically illustrates such an impulse response when a large power pulses are present in the decision feedback equalization region. Referring to FIG. 3, when the large power pulses are present in the decision feedback equalization region, the calculation error in the decision feedback equalization is increased as much as it is not negligible, because of a quantization error generated in the calculating circuit of the delayed decision feedback sequence estimator.
The second problem is in that the calculation by use of a complex algorithm is required until the optimum signal estimation region is determined.
FIG. 4 is an explanatory diagram for explaining such a state. As indicated in FIG. 4, the pulse amplitude values of the impulse response for the transmission channel are allocated with pulse numbers from the smallest number in order of larger pulse amplitude value until the optimum signal estimation region is determined. Thus, the amplitude values of pulses of the impulse response must be compared with each other. Further, the comparison process operation must be repeatedly carried out plural times in order to determine the optimum signal estimation region. As a result, the overall algorithm becomes complex. In particular, when the number of taps of the matching filter is increased, the calculation amount thereof is increased.